Here's who we talked to:
Uri Maoz, Head of U.S. Sales and Marketing, Anodot | Dave McCrory, CTO, Basho | Carl Tsukahara, CMO, Birst | Bob Vaillancourt, Vice President, CFB Strategies | Mikko Jarva, CTO Intelligent Data, Comptel | Sham Mustafa, Co-Founder and CEO, Correlation One | Andrew Brust, Senior Director Marketing Strategy, Datameer | Tarun Thakur, CEO/Co-Founder, Datos IO | Guy Yehiav, CEO, Profitect | Hjalmar Gislason, Vice President of Data, Qlik | Guy Levy-Yurista, Head of Product, Sisense | Girish Pancha, CEO, StreamSets | Ciaran Dynes, Vice Presidents of Products, Talend | Kim Hanmark, Director, Professional Services, TARGIT | Dennis Duckworth, Director of Product Marketing, VoltDB.
We asked these executives, "What have I failed to ask you that you think we need to consider with regard to big data?"
Here's what they told us:
- Everyone wants to adopt a newer framework. As the next generation tools come online what do we need to keep in mind from an application perspective with regards to cloud, scale, encryption, and security? What will help you guys have a better database virtualization layer?
- What are some new use cases given the capabilities of the platforms and the tools? Give developers the opportunities to use all of these new extensions and see what they’re able to come up with.
- Get a sense of developers’ awareness level as a baseline. How sophisticated and bought in are developers to big data?
- Traditional big data around predictive analytics. Now it’s more towards combining with traditional and interactive. Where do these two things come together? Where does the data science predictive analytics world align with business intelligence?
- We need more use cases so businesses can see the opportunities.
- The last six to 12 months I’ve been dropping “big” from “big data.” Systems will be able to handle the size, types and velocity of data. If the analytical tools don’t keep up with the changes they’ll fall by the wayside.
- The challenges of today’s world. The importance of products today covering the challenges and succeeding.
- Where are people placing their big data to do analytics – in the cloud, on premise, hybrid, local, global? What considerations are being taken around data movement? I believe in data gravity whereby large data should run as close to the host as possible. What are people doing with multi-tiered collection and processing?
- You didn’t ask about Blockchain. It’s on our radar since it will result in a sea change for economic transactions. It’s the next big topic to be hyped.
What other additional considerations do you have around big data?